February 1, 2019 An Overview of S+C Intelligence Fields and Methods

Welcome to Smith + Crown Intelligence (SCI)! In this overview, readers will find some context and clarification concerning the major fields displayed in Lantern and ‘Signal Status’, some details on how field and signals status are determined, information on values informing research methods, and some rationale behind current approaches. The information herein is designed to provide a summary, with more comprehensive accounts of research methodology available in select research pieces, planned releases, or through future community engagement.

The document is organized into four sections:

  1. Summary of Key Fields
  2. Summary of Signal Status
  3. Outline of the Signals’ Evaluation Process
  4. Principles behind Key Field Values

Earlier sections offer broader summaries and latter sections offer more narrow introductions to important nuances in method. The memo will introduce readers to key areas in S+C’s research methodology, and help direct more curious readers to further resources.

Summary of Key Fields

S+C collects data indicative of project performance and industry trends. Some of this data is made available through SCI. Key fields users encounter include:


Some further discussion of the caveats and assumptions underlying key SCI fields can be found in the ‘Principles behind Key Fields Values’ section below. Even more detailed discussion can be found in select S+C research articles, and in planned future releases. Sound research methodology sets organizations' findings apart, and S+C welcomes conversations on best practices in industry research methods. To participate in that conversation, please reach out to hello@smithandcrown.com.

Summary of Signal Status

Some projects in SCI are listed as ‘Signal’. Listing a project as ‘Signal’ is S+C’s way of distinguishing industry signal from noise. The following clarifies what it means to be ‘Signal’:


Outline of the Signals’ Evaluation Process

How research is conducted critically shapes the character of its products. S+C’s methods for evaluating Signals candidates contribute significantly to distinguishing the Signals lists from other available surveys of projects. The processes for including and changing Signals status is informed by S+C’s conception of good inquiry, which is committed to:

  • Minimizing personal bias.
  • Reflecting experts’ collective understanding of the industry’s current state.
  • Being responsive to reasons and evidence.
  • Remaining open to oversight, correction, and rational revision.
  • Making transparent grounds for Signal’s inclusion or exclusion.
  • Holding findings accountable to impacted parties: analysts, projects, and the general public can exercise oversight on Signal inclusion to varying degrees.

S+C invites discussion on these and other relevant guiding values, which users can participate in as part of future planned community engagement. These values shape the current Signals’ evaluation process and, along with practical considerations, inform decisions on changes to workflow.


Principles Behind Key Field Values

There are reasons why S+C uses the field values it does or calculates a sum a particular way. The rationale behind key classification and quantitative decisions is summarized here.

Project Status

The ‘Project Status’ field indicates the current state of a given project’s primary offering. The notion of a ‘primary offering’ is project-sensitive, with analyst’s judgments that a product B constitutes part of project A’s primary offering grounded in their understanding of both a project’s stated goals and stated steps for achieving those goals, as are found in a project’s whitepaper, website, blog, or communications to S+C. Broadly, S+C understands project status through the following framework:


Note also that S+C views project status holistically, and does not equate project status with token status. A project’s cryptoasset can be traded while a project is still developing the networks, Dapps, user-base, or industry relationships whose value the cryptoasset may (or may not) capture. While the incentive structure a cryptoeconomic system provides can be a necessary component of a project’s feature set, the release of a cryptoasset alone is typically insufficient for a change in project status.

Funding and Market Cap

The ‘Funding’ field indicates the total amount a project raised in its token sale. Values are given in the USD, converted from cryptocurrency using the relevant exchange rate at the conclusion of the sale.

Market Capitalization is the Circulating Supply * Current Price of a cryptoasset, and is roughly analogous to the identically-named metric in equity markets. This data is primarily sourced from the Nomics API, and updated every ten minutes.

Circulating Supply includes all tokens currently available to transact on-chain. It does not include tokens slated to be issued as future mining or staking rewards.

While Market Capitalization is the most frequent metric used to measure the value and network activity of public cryptoassets, it is imperfect for several reasons:

  • Varying inflation schedules – Investors may face significant dilution as inflation schedules vary widely between tokens.
  • Lost coins and discrepancies in circulating supply – The owners of some tokens, particularly from early Bitcoin mining and trading, may have lost private keys that render them permanently unrecoverable. These tokens are effectively removed from the circulating supply for price discovery purposes, but are counted as part of the supply in the standard calculation of Market Cap.
  • Liquidity – Tokens with low liquidity and thinly traded markets may have artificially inflated market caps.

While Market Cap is an imperfect metric as translated from the world of traditional equity, it does serve as a useful baseline for approximate valuation and an ordinal ranking of cryptoasset valuations. An array of emerging alternatives are discussed in this Nomics blog post, including “fully diluted market cap” with circulating supply normalized as the estimated value in 2050, and “realized value” to disregard lost coins by considering the exchange rate at which the token was last moved on-chain. We endeavor to provide and contextualize these evolving metrics to characterize a cryptoasset’s total value.


There have been many efforts to classify startups and blockchain projects by industry. Outlier Venture’s token ecosystem classification is particularly insightful. Classification serves multiple purposes, including helping cluster projects working on similar problems, identifying peer companies, and tracking growth over time. This helps identify which sectors are particularly dynamic, indicating a shared intuition of a particularly lucrative blockchain application.

Industry classification is not as straightforward as might initially appear. The most comprehensive efforts to classify business activity are usually undertaken by governments. In the United States, industries must register according to the NAICS code system, which generally resembles the International Industry Classification system.

There is one key decision in such classifications that the lay observer usually misses. Most systems categorize companies according to their means of production rather than their product. An example would be how Uber is classified as an information company rather than a transportation one, or Airbnb as an information company rather than an accommodation business.

From the standpoint of governments, this makes sense. Means of production is a better indicator of employment needs and industrial input–two areas over which governments have immense influence. Manufacturing cars requires different types of workers and resources than designing software to support car manufacturers. It has the added (and unintended) benefit of remaining mostly stable on a per-company basis: the software company could begin selling software to distributors (a different sector).

This approach also has several drawbacks: it is very poor at making sense of the technology sector, particularly information technology and its impacts throughout the economy. Under current production-oriented classification (like the NAICS system), a software company solely supporting car manufacturers would be considered a software company. If a car manufacturer acquires that company to perform the same services in-house, it would seem like the manufacturing sector grew and the software sector shrunk.

In addition, the actual products are important to keep track of as a means of identifying market changes. Governments have the luxury of tracking this through product sales numbers, but this isn’t always feasible. It also makes it difficult for companies to identify competitors or strategic threats. Airbnb undoubtedly has an impact on the accommodations industry. Finally, the commitment of means of production is also likely short-lived. On a certain level, every company is an information company.


Smith + Crown has considered this issue carefully as we develop our own estimations of blockchain-related activity across a range of industries and sectors, and we have implemented to following approach to classification.

  • Classify according to target market. What industry is the company trying to disrupt? In other words, if it is a payment system for marijuana, it operates in the drugs and alcohol sector.
  • If the project’s market is industry agnostic, classify according to its product. For example, if it is a general purpose payment system, it operates in payment processing sector.
  • Classify according to several new sectors that are specific to the blockchain industry, including smart contract platforms and prediction markets.
  • Finally, use the NAICS code industry system as a backend and maintain a cross-walk to new industry and sector classifications.

We have done so for the following reasons.

  1. Classification by means of production would be very difficult and usually arbitrary. Ultimately, most companies are applying blockchain technology in one of several ways: an immutable and auditable ledger, a digital currency, autonomous and auditable software, and an economic system for crowd contributions. Even these distinctions are rough and not comprehensive.
  2. It is a more coherent story of disruption. Classification by (arbitrarily chosen) means of production wouldn’t shed much insight into how blockchain technology is actually being used to disrupt traditional industries.
  3. It helps identify peers and competitors. This is important for assessing the relative merits of different tokens.
  4. It is more straightforward. Today, most blockchain companies are small. While they will pivot or expand their services, in their early stages they have a distinct focus that is usually easy to identify.